diseasome — Human disease network (diseasome, 2005)
- Description
Bipartite network of human genetic disorders and disease genes, from the "diseasome" of K.-I. Goh and collaborators, as distributed by the Gephi project. Nodes are disorders and genes, and an undirected edge connects a disorder to a gene whose mutations are associated with it. The disorder-gene associations were obtained from the Morbid Map of the Online Mendelian Inheritance in Man (OMIM) database (December 2005 version), in which the authors merged the subtypes of the same disorder into a single disorder and manually assigned each disorder to one of 22 classes according to the physiological system affected. This version contains the 516 disorders of the giant component of the human disease network (the projection in which two disorders are connected if they share a gene), and 903 disease genes connected to them.
The source file also contains the edges of this projection (two disorders connected if they share at least one gene, each listed twice); they are not included here, since they can be obtained from the bipartite network.
The nodes have the following properties:
name: the name of the disorder (e.g. "Alzheimer disease"), or the symbol of the gene.is_disorder: whether the node is a disorder (otherwise it is a gene).disorder_class: the class of the disorder (e.g. "Cancer", "Neurological", "Multiple"), as given in the source (with its spelling, e.g. "Ophthamological"); empty for genes.1
- Tags
- Biological Unweighted Metadata
- Citation
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- K.-I. Goh, M. E. Cusick, D. Valle, B. Childs, M. Vidal, A.-L. Barabási, "The human disease network." Proceedings of the National Academy of Sciences 104(21), 8685-8690 (2007) 10.1073/pnas.0701361104 Sci-Hub
- Upstream URL OK
- https://github.com/gephi/gephi/wiki/Datasets
- Networks
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Tip: hover over a column header for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties